Overview

Dataset statistics

Number of variables10
Number of observations530
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.1 KiB
Average record size in memory81.2 B

Variable types

Numeric1
Categorical4
DateTime1
Text4

Dataset

Description석유품질관리지원협약이란 주유소가 판매하는 석유 제품의 품질을 관리함으로써 소비자가 믿고 이용할 수 있는 주유소를 활성화하여 국내 석유시장의 건전한 유통질서 확립에 기여하기 위한 제도입니다.이 데이터는 석유품질관리 지원 사업 협약주유소 관련 데이터로 주유소명, 지역, 주소, 품질검사 적합 여부 등의 정보 확인이 가능합니다.
Author한국석유관리원
URLhttps://www.data.go.kr/data/3048810/fileData.do

Alerts

품질 적합 여부 has constant value ""Constant
구분 is highly imbalanced (71.9%)Imbalance
순번 has unique valuesUnique

Reproduction

Analysis started2024-04-21 02:43:26.075930
Analysis finished2024-04-21 02:43:28.163351
Duration2.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct530
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean265.5
Minimum1
Maximum530
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2024-04-21T11:43:28.248843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile27.45
Q1133.25
median265.5
Q3397.75
95-th percentile503.55
Maximum530
Range529
Interquartile range (IQR)264.5

Descriptive statistics

Standard deviation153.14209
Coefficient of variation (CV)0.57680637
Kurtosis-1.2
Mean265.5
Median Absolute Deviation (MAD)132.5
Skewness0
Sum140715
Variance23452.5
MonotonicityStrictly increasing
2024-04-21T11:43:28.385312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
350 1
 
0.2%
364 1
 
0.2%
363 1
 
0.2%
362 1
 
0.2%
361 1
 
0.2%
360 1
 
0.2%
359 1
 
0.2%
358 1
 
0.2%
357 1
 
0.2%
Other values (520) 520
98.1%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
530 1
0.2%
529 1
0.2%
528 1
0.2%
527 1
0.2%
526 1
0.2%
525 1
0.2%
524 1
0.2%
523 1
0.2%
522 1
0.2%
521 1
0.2%

본부
Categorical

Distinct10
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
대경
100 
부울경
71 
수남
66 
대세충
60 
광전
48 
Other values (5)
185 

Length

Max length3
Median length2
Mean length2.2471698
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row광전
2nd row대경
3rd row수남
4th row광전
5th row수남

Common Values

ValueCountFrequency (%)
대경 100
18.9%
부울경 71
13.4%
수남 66
12.5%
대세충 60
11.3%
광전 48
9.1%
전북 47
8.9%
충북 45
8.5%
강원 41
7.7%
수북 33
 
6.2%
제주 19
 
3.6%

Length

2024-04-21T11:43:28.514177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:43:28.627305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대경 100
18.9%
부울경 71
13.4%
수남 66
12.5%
대세충 60
11.3%
광전 48
9.1%
전북 47
8.9%
충북 45
8.5%
강원 41
7.7%
수북 33
 
6.2%
제주 19
 
3.6%

협약연도
Date

Distinct169
Distinct (%)31.9%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum2023-03-14 00:00:00
Maximum2024-04-01 00:00:00
2024-04-21T11:43:28.767411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:43:28.899744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

주유소명
Text

Distinct526
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-04-21T11:43:29.136480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length7.445283
Min length1

Characters and Unicode

Total characters3946
Distinct characters313
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique522 ?
Unique (%)98.5%

Sample

1st row한국도로공사 백양사(논산)
2nd row유남석유㈜
3rd row하남만남
4th row백양사(하)
5th row이동농협
ValueCountFrequency (%)
한국도로공사 8
 
1.2%
대보유통㈜ 6
 
0.9%
주식회사 6
 
0.9%
대보건설㈜ 5
 
0.7%
㈜바이오시스 5
 
0.7%
ym21유통㈜ 3
 
0.4%
주)한라석유 3
 
0.4%
씨앤에스에너지(주 3
 
0.4%
kis정보통신㈜ 3
 
0.4%
주)경인석유고속도로 3
 
0.4%
Other values (606) 646
93.5%
2024-04-21T11:43:29.505762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 227
 
5.8%
( 227
 
5.8%
농 202
 
5.1%
협 202
 
5.1%
167
 
4.2%
주 111
 
2.8%
㈜ 104
 
2.6%
산 100
 
2.5%
향 69
 
1.7%
천 66
 
1.7%
Other values (303) 2471
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3164
80.2%
Close Punctuation 227
 
5.8%
Open Punctuation 227
 
5.8%
Space Separator 167
 
4.2%
Other Symbol 104
 
2.6%
Decimal Number 27
 
0.7%
Uppercase Letter 24
 
0.6%
Connector Punctuation 3
 
0.1%
Lowercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 202
 
6.4%
협 202
 
6.4%
주 111
 
3.5%
산 100
 
3.2%
향 69
 
2.2%
천 66
 
2.1%
방 65
 
2.1%
유 64
 
2.0%
대 57
 
1.8%
서 52
 
1.6%
Other values (281) 2176
68.8%
Decimal Number
ValueCountFrequency (%)
1 9
33.3%
0 7
25.9%
2 5
18.5%
8 2
 
7.4%
7 1
 
3.7%
6 1
 
3.7%
3 1
 
3.7%
5 1
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
K 5
20.8%
I 5
20.8%
S 5
20.8%
Y 4
16.7%
M 4
16.7%
C 1
 
4.2%
Lowercase Letter
ValueCountFrequency (%)
s 1
33.3%
i 1
33.3%
k 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 227
100.0%
Open Punctuation
ValueCountFrequency (%)
( 227
100.0%
Space Separator
ValueCountFrequency (%)
167
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 104
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3268
82.8%
Common 651
 
16.5%
Latin 27
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 202
 
6.2%
협 202
 
6.2%
주 111
 
3.4%
㈜ 104
 
3.2%
산 100
 
3.1%
향 69
 
2.1%
천 66
 
2.0%
방 65
 
2.0%
유 64
 
2.0%
대 57
 
1.7%
Other values (282) 2228
68.2%
Common
ValueCountFrequency (%)
) 227
34.9%
( 227
34.9%
167
25.7%
1 9
 
1.4%
0 7
 
1.1%
2 5
 
0.8%
_ 3
 
0.5%
8 2
 
0.3%
7 1
 
0.2%
6 1
 
0.2%
Other values (2) 2
 
0.3%
Latin
ValueCountFrequency (%)
K 5
18.5%
I 5
18.5%
S 5
18.5%
Y 4
14.8%
M 4
14.8%
s 1
 
3.7%
i 1
 
3.7%
C 1
 
3.7%
k 1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3164
80.2%
ASCII 678
 
17.2%
None 104
 
2.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 227
33.5%
( 227
33.5%
167
24.6%
1 9
 
1.3%
0 7
 
1.0%
K 5
 
0.7%
I 5
 
0.7%
S 5
 
0.7%
2 5
 
0.7%
Y 4
 
0.6%
Other values (11) 17
 
2.5%
Hangul
ValueCountFrequency (%)
농 202
 
6.4%
협 202
 
6.4%
주 111
 
3.5%
산 100
 
3.2%
향 69
 
2.2%
천 66
 
2.1%
방 65
 
2.1%
유 64
 
2.0%
대 57
 
1.8%
서 52
 
1.6%
Other values (281) 2176
68.8%
None
ValueCountFrequency (%)
㈜ 104
100.0%

대표자
Text

Distinct393
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-04-21T11:43:29.792285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.245283
Min length2

Characters and Unicode

Total characters1720
Distinct characters168
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique328 ?
Unique (%)61.9%

Sample

1st row함진규
2nd row최영자
3rd row정승환
4th row김봉수
5th row어준선
ValueCountFrequency (%)
외 27
 
4.6%
1명 15
 
2.6%
김진경 12
 
2.1%
2명 11
 
1.9%
함진규 9
 
1.5%
심광보 8
 
1.4%
김승현 7
 
1.2%
황종현 6
 
1.0%
김원태 6
 
1.0%
남영선 6
 
1.0%
Other values (383) 478
81.7%
2024-04-21T11:43:30.178082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 118
 
6.9%
이 69
 
4.0%
58
 
3.4%
정 47
 
2.7%
명 44
 
2.6%
박 40
 
2.3%
진 40
 
2.3%
영 39
 
2.3%
수 36
 
2.1%
최 35
 
2.0%
Other values (158) 1194
69.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1635
95.1%
Space Separator 58
 
3.4%
Decimal Number 27
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 118
 
7.2%
이 69
 
4.2%
정 47
 
2.9%
명 44
 
2.7%
박 40
 
2.4%
진 40
 
2.4%
영 39
 
2.4%
수 36
 
2.2%
최 35
 
2.1%
경 31
 
1.9%
Other values (154) 1136
69.5%
Decimal Number
ValueCountFrequency (%)
1 15
55.6%
2 11
40.7%
3 1
 
3.7%
Space Separator
ValueCountFrequency (%)
58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1635
95.1%
Common 85
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 118
 
7.2%
이 69
 
4.2%
정 47
 
2.9%
명 44
 
2.7%
박 40
 
2.4%
진 40
 
2.4%
영 39
 
2.4%
수 36
 
2.2%
최 35
 
2.1%
경 31
 
1.9%
Other values (154) 1136
69.5%
Common
ValueCountFrequency (%)
58
68.2%
1 15
 
17.6%
2 11
 
12.9%
3 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1635
95.1%
ASCII 85
 
4.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 118
 
7.2%
이 69
 
4.2%
정 47
 
2.9%
명 44
 
2.7%
박 40
 
2.4%
진 40
 
2.4%
영 39
 
2.4%
수 36
 
2.2%
최 35
 
2.1%
경 31
 
1.9%
Other values (154) 1136
69.5%
ASCII
ValueCountFrequency (%)
58
68.2%
1 15
 
17.6%
2 11
 
12.9%
3 1
 
1.2%

구분
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
갱신
483 
신규
 
46
휴업
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row갱신
2nd row갱신
3rd row갱신
4th row갱신
5th row갱신

Common Values

ValueCountFrequency (%)
갱신 483
91.1%
신규 46
 
8.7%
휴업 1
 
0.2%

Length

2024-04-21T11:43:30.293123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:43:30.380155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
갱신 483
91.1%
신규 46
 
8.7%
휴업 1
 
0.2%

주소(전체)
Text

Distinct526
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-04-21T11:43:30.666378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length19.837736
Min length12

Characters and Unicode

Total characters10514
Distinct characters297
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique522 ?
Unique (%)98.5%

Sample

1st row전남 장성군 호남고속도로 108-1 (북일면)
2nd row경북 칠곡군 왜관읍 경부고속도로 159
3rd row경기 하남시 중부고속도로 117-1
4th row전남 장성군 북이면 호남고속도로 107
5th row경기 용인시 처인구 이동면 백옥대로 96
ValueCountFrequency (%)
경기 86
 
3.4%
경북 69
 
2.7%
경남 53
 
2.1%
충남 47
 
1.9%
전북 47
 
1.9%
전남 43
 
1.7%
충북 43
 
1.7%
강원 37
 
1.5%
청주시 19
 
0.8%
제주 18
 
0.7%
Other values (1265) 2055
81.6%
2024-04-21T11:43:31.108787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2038
 
19.4%
로 482
 
4.6%
1 343
 
3.3%
시 331
 
3.1%
경 272
 
2.6%
면 257
 
2.4%
남 220
 
2.1%
북 218
 
2.1%
2 218
 
2.1%
군 208
 
2.0%
Other values (287) 5927
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6436
61.2%
Space Separator 2038
 
19.4%
Decimal Number 1708
 
16.2%
Close Punctuation 126
 
1.2%
Open Punctuation 125
 
1.2%
Dash Punctuation 81
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 482
 
7.5%
시 331
 
5.1%
경 272
 
4.2%
면 257
 
4.0%
남 220
 
3.4%
북 218
 
3.4%
군 208
 
3.2%
주 182
 
2.8%
도 160
 
2.5%
산 149
 
2.3%
Other values (273) 3957
61.5%
Decimal Number
ValueCountFrequency (%)
1 343
20.1%
2 218
12.8%
3 192
11.2%
4 152
8.9%
7 151
8.8%
5 146
8.5%
0 144
8.4%
8 128
 
7.5%
6 119
 
7.0%
9 115
 
6.7%
Space Separator
ValueCountFrequency (%)
2038
100.0%
Close Punctuation
ValueCountFrequency (%)
) 126
100.0%
Open Punctuation
ValueCountFrequency (%)
( 125
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6436
61.2%
Common 4078
38.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 482
 
7.5%
시 331
 
5.1%
경 272
 
4.2%
면 257
 
4.0%
남 220
 
3.4%
북 218
 
3.4%
군 208
 
3.2%
주 182
 
2.8%
도 160
 
2.5%
산 149
 
2.3%
Other values (273) 3957
61.5%
Common
ValueCountFrequency (%)
2038
50.0%
1 343
 
8.4%
2 218
 
5.3%
3 192
 
4.7%
4 152
 
3.7%
7 151
 
3.7%
5 146
 
3.6%
0 144
 
3.5%
8 128
 
3.1%
) 126
 
3.1%
Other values (4) 440
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6436
61.2%
ASCII 4078
38.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2038
50.0%
1 343
 
8.4%
2 218
 
5.3%
3 192
 
4.7%
4 152
 
3.7%
7 151
 
3.7%
5 146
 
3.6%
0 144
 
3.5%
8 128
 
3.1%
) 126
 
3.1%
Other values (4) 440
 
10.8%
Hangul
ValueCountFrequency (%)
로 482
 
7.5%
시 331
 
5.1%
경 272
 
4.2%
면 257
 
4.0%
남 220
 
3.4%
북 218
 
3.4%
군 208
 
3.2%
주 182
 
2.8%
도 160
 
2.5%
산 149
 
2.3%
Other values (273) 3957
61.5%

전화번호
Text

Distinct522
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2024-04-21T11:43:31.340365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.00566
Min length11

Characters and Unicode

Total characters6363
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique514 ?
Unique (%)97.0%

Sample

1st row061-393-0267
2nd row054-975-1734
3rd row031-793-5800
4th row061-394-5178
5th row031-336-8272
ValueCountFrequency (%)
070-4304-0610 2
 
0.4%
033-344-3430 2
 
0.4%
053-851-6110 2
 
0.4%
052-977-3243 2
 
0.4%
043-844-2988 2
 
0.4%
054-823-5182 2
 
0.4%
070-4304-0630 2
 
0.4%
055-854-6732 2
 
0.4%
031-759-0178 1
 
0.2%
031-498-0051 1
 
0.2%
Other values (512) 512
96.6%
2024-04-21T11:43:31.702486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1060
16.7%
0 886
13.9%
3 761
12.0%
5 704
11.1%
1 582
9.1%
4 561
8.8%
6 451
7.1%
2 418
 
6.6%
8 374
 
5.9%
7 351
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5303
83.3%
Dash Punctuation 1060
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 886
16.7%
3 761
14.4%
5 704
13.3%
1 582
11.0%
4 561
10.6%
6 451
8.5%
2 418
7.9%
8 374
7.1%
7 351
 
6.6%
9 215
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 1060
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6363
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1060
16.7%
0 886
13.9%
3 761
12.0%
5 704
11.1%
1 582
9.1%
4 561
8.8%
6 451
7.1%
2 418
 
6.6%
8 374
 
5.9%
7 351
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6363
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1060
16.7%
0 886
13.9%
3 761
12.0%
5 704
11.1%
1 582
9.1%
4 561
8.8%
6 451
7.1%
2 418
 
6.6%
8 374
 
5.9%
7 351
 
5.5%

상표
Categorical

Distinct6
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
농협
202 
도로공사
181 
석유공사
136 
현대
 
5
비상표
 
5

Length

Max length5
Median length4
Mean length3.2113208
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row도로공사
2nd row도로공사
3rd row도로공사
4th row도로공사
5th row농협

Common Values

ValueCountFrequency (%)
농협 202
38.1%
도로공사 181
34.2%
석유공사 136
25.7%
현대 5
 
0.9%
비상표 5
 
0.9%
S-oil 1
 
0.2%

Length

2024-04-21T11:43:31.829812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:43:31.942772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농협 202
38.1%
도로공사 181
34.2%
석유공사 136
25.7%
현대 5
 
0.9%
비상표 5
 
0.9%
s-oil 1
 
0.2%

품질 적합 여부
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
적합
530 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row적합
2nd row적합
3rd row적합
4th row적합
5th row적합

Common Values

ValueCountFrequency (%)
적합 530
100.0%

Length

2024-04-21T11:43:32.048719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:43:32.138372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적합 530
100.0%

Interactions

2024-04-21T11:43:27.801244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:43:32.210597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번본부구분상표
순번1.0000.3010.5550.293
본부0.3011.0000.1370.246
구분0.5550.1371.0000.371
상표0.2930.2460.3711.000
2024-04-21T11:43:32.296390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분상표본부
구분1.0000.1650.081
상표0.1651.0000.131
본부0.0810.1311.000
2024-04-21T11:43:32.401521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번본부구분상표
순번1.0000.0960.3960.158
본부0.0961.0000.0810.131
구분0.3960.0811.0000.165
상표0.1580.1310.1651.000

Missing values

2024-04-21T11:43:27.971037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:43:28.097958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

순번본부협약연도주유소명대표자구분주소(전체)전화번호상표품질 적합 여부
01광전2024-01-18한국도로공사 백양사(논산)함진규갱신전남 장성군 호남고속도로 108-1 (북일면)061-393-0267도로공사적합
12대경2024-01-23유남석유㈜최영자갱신경북 칠곡군 왜관읍 경부고속도로 159054-975-1734도로공사적합
23수남2024-01-25하남만남정승환갱신경기 하남시 중부고속도로 117-1031-793-5800도로공사적합
34광전2024-01-26백양사(하)김봉수갱신전남 장성군 북이면 호남고속도로 107061-394-5178도로공사적합
45수남2024-01-29이동농협어준선갱신경기 용인시 처인구 이동면 백옥대로 96031-336-8272농협적합
56제주2024-01-29편리한전승엽갱신제주 제주시 중앙로 487064-724-5123석유공사적합
67충북2024-01-29칠성알뜰박진호갱신충북 괴산군 칠성면 중부로 5609043-832-5042석유공사적합
78대세충2024-01-29장등김은수갱신충남 서산시 지곡면 충의로 1546041-662-0340석유공사적합
89강원2024-01-29문막(하)고광선갱신강원 원주시 문막읍 원문로 1234-1033-734-0764도로공사적합
910대경2024-02-01양남농협경제사업장백민석갱신경북 경주시 양남면 동해안로 445054-749-4011농협적합
순번본부협약연도주유소명대표자구분주소(전체)전화번호상표품질 적합 여부
520521수남2023-12-27대신농협클린이용주갱신경기 여주시 대신면 여양로 1537031-884-3948농협적합
521522수북2023-12-27연천농협임철진갱신경기 연천군 연천읍 평화로 1211031-834-5188농협적합
522523전북2023-12-28오수(완주방향)김동훈갱신전북 임실군 오수면 순천완주고속도로 74063-644-4800도로공사적합
523524전북2023-12-28오수(순천방향)김동훈갱신전북 임실군 오수면 순천완주고속도로 73063-644-7300도로공사적합
524525부울경2023-12-16의령농협클린이용택갱신경남 의령군 의병로 171055-573-8711농협적합
525526전북2023-12-16대보유통㈜ 부안(서울)김진경갱신전북 부안군 주산면 서해안고속도로 106063-776-7088도로공사적합
526527전북2023-12-16대보유통㈜ 부안(목포)김진경갱신전북 부안군 주산면 서해안고속도로 103063-776-8088도로공사적합
527528강원2023-12-16키다리식품(주) 내린천(서울)이명수갱신강원 인제군 상남면 서울양양고속도로117033-852-7110도로공사적합
528529강원2023-12-16키다리식품(주) 내린천(양양)이명수갱신강원 인제군 상남면 서울양양고속도로117-1033-852-7220도로공사적합
529530대경2023-12-15천지김천수 외 1명신규대구광역시 북구 사수로369 (금호동)053-312-0072석유공사적합